diff options
Diffstat (limited to 'lib/leave-one-out-validation.rb')
| -rw-r--r-- | lib/leave-one-out-validation.rb | 41 |
1 files changed, 18 insertions, 23 deletions
diff --git a/lib/leave-one-out-validation.rb b/lib/leave-one-out-validation.rb index c33c92b..7d73b89 100644 --- a/lib/leave-one-out-validation.rb +++ b/lib/leave-one-out-validation.rb @@ -9,25 +9,18 @@ module OpenTox # @param [OpenTox::Model::Lazar] # @return [OpenTox::Validation::LeaveOneOut] def self.create model - bad_request_error "Cannot create leave one out validation for models with supervised feature selection. Please use crossvalidation instead." if model.algorithms[:feature_selection] + raise ArgumentError, "Cannot create leave one out validation for models with supervised feature selection. Please use crossvalidation instead." if model.algorithms[:feature_selection] $logger.debug "#{model.name}: LOO validation started" t = Time.now - model.training_dataset.features.first.nominal? ? klass = ClassificationLeaveOneOut : klass = RegressionLeaveOneOut + model.training_dataset.features.collect{|f| f.class}.include?(NominalBioActivity) ? klass = ClassificationLeaveOneOut : klass = RegressionLeaveOneOut loo = klass.new :model_id => model.id predictions = model.predict model.training_dataset.substances predictions.each{|cid,p| p.delete(:neighbors)} - nr_unpredicted = 0 predictions.each do |cid,prediction| - if prediction[:value] - prediction[:measurements] = model.training_dataset.values(cid, prediction[:prediction_feature_id]) - else - nr_unpredicted += 1 - end + prediction[:measurements] = model.training_dataset.values(cid, prediction[:prediction_feature_id]) if prediction[:value] predictions.delete(cid) unless prediction[:value] and prediction[:measurements] end predictions.select!{|cid,p| p[:value] and p[:measurements]} - loo.nr_instances = predictions.size - loo.nr_unpredicted = nr_unpredicted loo.predictions = predictions loo.statistics $logger.debug "#{model.name}, LOO validation: #{Time.now-t} seconds" @@ -40,25 +33,27 @@ module OpenTox class ClassificationLeaveOneOut < LeaveOneOut include ClassificationStatistics field :accept_values, type: Array - field :confusion_matrix, type: Array, default: [] - field :weighted_confusion_matrix, type: Array, default: [] - field :accuracy, type: Float - field :weighted_accuracy, type: Float - field :true_rate, type: Hash, default: {} - field :predictivity, type: Hash, default: {} - field :confidence_plot_id, type: BSON::ObjectId + field :confusion_matrix, type: Hash + field :weighted_confusion_matrix, type: Hash + field :accuracy, type: Hash + field :weighted_accuracy, type: Hash + field :true_rate, type: Hash + field :predictivity, type: Hash + field :nr_predictions, type: Hash + field :probability_plot_id, type: BSON::ObjectId end # Leave one out validation for regression models class RegressionLeaveOneOut < LeaveOneOut include RegressionStatistics - field :rmse, type: Float, default: 0 - field :mae, type: Float, default: 0 - field :r_squared, type: Float - field :within_prediction_interval, type: Integer, default:0 - field :out_of_prediction_interval, type: Integer, default:0 - field :correlation_plot_id, type: BSON::ObjectId + field :rmse, type: Hash + field :mae, type: Hash + field :r_squared, type: Hash + field :within_prediction_interval, type: Hash + field :out_of_prediction_interval, type: Hash + field :nr_predictions, type: Hash field :warnings, type: Array + field :correlation_plot_id, type: BSON::ObjectId end end |